説明可能AI（XAI）による状況認識の透明化¶

// SHAP・LIME統合説明システム
interface ComprehensiveExplanation {
  predictionId: string;
  timestamp: Date;
  shapExplanation: SHAPExplanation;
  limeExplanation: LIMEExplanation;
  integratedExplanation: IntegratedExplanation;
  confidenceMetrics: ConfidenceMetrics;
  visualizations: ExplanationVisualization[];
}

interface SHAPExplanation {
  featureImportances: FeatureImportance[];
  baseValue: number;
  shapValues: number[];
  interactionEffects: InteractionEffect[];
  globalImportance: GlobalImportance[];
}

interface LIMEExplanation {
  localModel: LocalModel;
  featureWeights: FeatureWeight[];
  neighborhoodSize: number;
  fidelity: number;
  localAccuracy: number;
}

interface IntegratedExplanation {
  consensusFeatures: ConsensusFeature[];
  conflictingFeatures: ConflictingFeature[];
  overallConfidence: number;
  explanationQuality: ExplanationQuality;
  humanReadableExplanation: string;
}

class SHAPLIMEExplanationSystem {
  private shapExplainer: SHAPExplainer;
  private limeExplainer: LIMEExplainer;
  private integrationEngine: ExplanationIntegrationEngine;
  private visualizationEngine: ExplanationVisualizationEngine;
  private confidenceCalculator: ExplanationConfidenceCalculator;

  constructor() {
    this.initializeExplainers();
    this.setupReactiveExplanationPipeline();
  }

  private initializeExplainers(): void {
    // SHAP説明器の初期化
    this.shapExplainer = new SHAPExplainer({
      explainerType: 'tree', // 'tree', 'linear', 'deep', 'kernel'
      numSamples: 1000,
      checkAdditivity: true,
      featureNames: this.getFeatureNames()
    });

    // LIME説明器の初期化
    this.limeExplainer = new LIMEExplainer({
      mode: 'classification', // 'classification', 'regression'
      numFeatures: 20,
      numSamples: 5000,
      distance_metric: 'cosine',
      kernelWidth: 0.25
    });

    // 説明統合エンジン
    this.integrationEngine = new ExplanationIntegrationEngine({
      weightingStrategy: 'confidence_weighted',
      conflictResolution: 'ensemble_voting',
      consistencyThreshold: 0.8
    });

    // 可視化エンジン
    this.visualizationEngine = new ExplanationVisualizationEngine({
      chartTypes: ['waterfall', 'force_plot', 'summary_plot', 'decision_plot'],
      interactivity: true,
      responsiveDesign: true
    });
  }

  // リアクティブ説明生成パイプライン
  private setupReactiveExplanationPipeline(): void {
    // 説明要求のストリーム
    this.explanationRequests$ = new Subject<ExplanationRequest>();

    // 並列説明生成
    this.explanationResults$ = this.explanationRequests$.pipe(
      // 重複リクエストの除去
      distinctUntilChanged((a, b) => a.predictionId === b.predictionId),

      // 並列でSHAPとLIME説明を生成
      mergeMap(request => 
        forkJoin({
          shapResult: this.generateSHAPExplanation(request),
          limeResult: this.generateLIMEExplanation(request),
          metadata: of(request)
        }).pipe(
          // タイムアウト処理
          timeout(30000),
          catchError(error => of({
            shapResult: null,
            limeResult: null,
            metadata: request,
            error: error.message
          }))
        )
      ),

      // 結果の統合
      map(({ shapResult, limeResult, metadata, error }) => {
        if (error) {
          return { error, metadata };
        }

        return this.integrateExplanations(
          shapResult,
          limeResult,
          metadata
        );
      }),

      // 結果の共有
      share()
    );
  }

  // 包括的説明の生成
  async generateComprehensiveExplanation(
    prediction: MLPrediction,
    inputData: any,
    model: MLModel
  ): Promise<ComprehensiveExplanation> {
    // 説明要求の作成
    const explanationRequest: ExplanationRequest = {
      predictionId: prediction.id,
      prediction: prediction,
      inputData: inputData,
      model: model,
      timestamp: new Date()
    };

    // リアクティブパイプラインに要求を送信
    this.explanationRequests$.next(explanationRequest);

    // 結果の取得
    const result = await this.explanationResults$.pipe(
      filter(result => result.metadata?.predictionId === prediction.id),
      take(1)
    ).toPromise();

    if (result.error) {
      throw new Error(`説明生成エラー: ${result.error}`);
    }

    return result as ComprehensiveExplanation;
  }

  // SHAP説明の生成
  private async generateSHAPExplanation(
    request: ExplanationRequest
  ): Promise<SHAPExplanation> {
    // SHAP値の計算
    const shapValues = await this.shapExplainer.explainInstance(
      request.inputData,
      request.model
    );

    // 特徴量重要度の計算
    const featureImportances = this.calculateFeatureImportances(shapValues);

    // 相互作用効果の分析
    const interactionEffects = await this.analyzeInteractionEffects(
      request.inputData,
      request.model
    );

    // グローバル重要度の計算
    const globalImportance = await this.calculateGlobalImportance(
      request.model
    );

    return {
      featureImportances,
      baseValue: shapValues.baseValue,
      shapValues: shapValues.values,
      interactionEffects,
      globalImportance
    };
  }

  // LIME説明の生成
  private async generateLIMEExplanation(
    request: ExplanationRequest
  ): Promise<LIMEExplanation> {
    // 近傍データの生成
    const neighborhood = this.generateNeighborhood(
      request.inputData,
      this.limeExplainer.numSamples
    );

    // ローカルモデルの学習
    const localModel = await this.trainLocalModel(
      neighborhood,
      request.model
    );

    // 特徴量重みの計算
    const featureWeights = this.extractFeatureWeights(localModel);

    // 忠実度の評価
    const fidelity = this.calculateFidelity(
      localModel,
      request.model,
      neighborhood
    );

    return {
      localModel,
      featureWeights,
      neighborhoodSize: neighborhood.length,
      fidelity,
      localAccuracy: localModel.accuracy
    };
  }

  // 説明の統合
  private integrateExplanations(
    shapResult: SHAPExplanation,
    limeResult: LIMEExplanation,
    request: ExplanationRequest
  ): ComprehensiveExplanation {
    // 合意特徴量の特定
    const consensusFeatures = this.findConsensusFeatures(
      shapResult.featureImportances,
      limeResult.featureWeights
    );

    // 矛盾特徴量の特定
    const conflictingFeatures = this.findConflictingFeatures(
      shapResult.featureImportances,
      limeResult.featureWeights
    );

    // 統合説明の生成
    const integratedExplanation = this.generateIntegratedExplanation(
      consensusFeatures,
      conflictingFeatures,
      shapResult,
      limeResult
    );

    // 信頼度指標の計算
    const confidenceMetrics = this.calculateConfidenceMetrics(
      shapResult,
      limeResult,
      integratedExplanation
    );

    // 可視化の生成
    const visualizations = this.generateVisualizations(
      shapResult,
      limeResult,
      integratedExplanation
    );

    return {
      predictionId: request.predictionId,
      timestamp: new Date(),
      shapExplanation: shapResult,
      limeExplanation: limeResult,
      integratedExplanation,
      confidenceMetrics,
      visualizations
    };
  }

  // 対話的説明の生成
  async generateInteractiveExplanation(
    explanation: ComprehensiveExplanation,
    userQuery: string
  ): Promise<InteractiveExplanationResponse> {
    // ユーザークエリの解析
    const queryIntent = await this.analyzeUserQuery(userQuery);

    switch (queryIntent.type) {
      case 'feature_importance':
        return this.explainFeatureImportance(
          explanation,
          queryIntent.targetFeature
        );

      case 'counterfactual':
        return this.generateCounterfactualExplanation(
          explanation,
          queryIntent.desiredOutcome
        );

      case 'confidence':
        return this.explainConfidence(explanation);

      case 'comparison':
        return this.compareWithSimilarCases(
          explanation,
          queryIntent.comparisonTarget
        );

      default:
        return this.generateGeneralExplanation(explanation);
    }
  }

  // 反実仮想説明の生成
  private async generateCounterfactualExplanation(
    explanation: ComprehensiveExplanation,
    desiredOutcome: any
  ): Promise<CounterfactualExplanation> {
    // 最小変更による反実仮想例の生成
    const counterfactuals = await this.findMinimalCounterfactuals(
      explanation,
      desiredOutcome
    );

    // 変更可能性の評価
    const feasibility = this.assessCounterfactualFeasibility(
      counterfactuals
    );

    // 自然言語での説明生成
    const naturalLanguageExplanation = this.generateCounterfactualNarrative(
      counterfactuals,
      feasibility
    );

    return {
      counterfactualExamples: counterfactuals,
      feasibilityAssessment: feasibility,
      explanation: naturalLanguageExplanation,
      confidence: this.calculateCounterfactualConfidence(counterfactuals)
    };
  }

  // 時系列説明の生成
  async generateTimeSeriesExplanation(
    timeSeriesPredictions: TimeSeriesPrediction[],
    explanationWindow: number = 10
  ): Promise<TimeSeriesExplanation> {
    // ウィンドウごとの説明生成
    const windowExplanations = await Promise.all(
      this.createTimeWindows(timeSeriesPredictions, explanationWindow)
        .map(window => this.explainTimeWindow(window))
    );

    // 時系列パターンの分析
    const temporalPatterns = this.analyzeTemporalPatterns(
      windowExplanations
    );

    // 変化点の検出と説明
    const changePoints = this.detectAndExplainChangePoints(
      timeSeriesPredictions,
      windowExplanations
    );

    // トレンドの説明
    const trendExplanation = this.explainTrends(
      temporalPatterns,
      changePoints
    );

    return {
      windowExplanations,
      temporalPatterns,
      changePoints,
      trendExplanation,
      overallConfidence: this.calculateTimeSeriesExplanationConfidence(
        windowExplanations
      )
    };
  }

  // 説明品質の評価
  async evaluateExplanationQuality(
    explanation: ComprehensiveExplanation,
    groundTruth?: GroundTruthExplanation
  ): Promise<ExplanationQualityMetrics> {
    // 一貫性の評価
    const consistency = this.evaluateConsistency(
      explanation.shapExplanation,
      explanation.limeExplanation
    );

    // 安定性の評価
    const stability = await this.evaluateStability(explanation);

    // 完全性の評価
    const completeness = this.evaluateCompleteness(explanation);

    // 理解しやすさの評価
    const comprehensibility = this.evaluateComprehensibility(
      explanation.integratedExplanation
    );

    // グラウンドトゥルースとの比較（利用可能な場合）
    let faithfulness = null;
    if (groundTruth) {
      faithfulness = this.evaluateFaithfulness(explanation, groundTruth);
    }

    return {
      consistency,
      stability,
      completeness,
      comprehensibility,
      faithfulness,
      overallQuality: this.calculateOverallQuality({
        consistency,
        stability,
        completeness,
        comprehensibility
      })
    };
  }
}

// 結果インターフェース
interface InteractiveExplanationResponse {
  queryType: string;
  explanation: string;
  visualizations: Visualization[];
  followUpSuggestions: string[];
  confidence: number;
}

interface CounterfactualExplanation {
  counterfactualExamples: CounterfactualExample[];
  feasibilityAssessment: FeasibilityAssessment;
  explanation: string;
  confidence: number;
}

interface TimeSeriesExplanation {
  windowExplanations: WindowExplanation[];
  temporalPatterns: TemporalPattern[];
  changePoints: ChangePoint[];
  trendExplanation: TrendExplanation;
  overallConfidence: number;
}

// 注意機構可視化システム
interface AttentionVisualizationResult {
  modelId: string;
  inputId: string;
  timestamp: Date;
  attentionMaps: AttentionMap[];
  aggregatedAttention: AggregatedAttention;
  interpretations: AttentionInterpretation[];
  interactiveElements: InteractiveElement[];
}

interface AttentionMap {
  layerIndex: number;
  headIndex?: number;
  attentionType: 'self' | 'cross' | 'global';
  weights: number[][];
  inputTokens: string[];
  outputTokens: string[];
  heatmapData: HeatmapData;
}

interface AggregatedAttention {
  globalAttention: number[];
  layerWiseAttention: LayerWiseAttention[];
  headRoleAnalysis: HeadRoleAnalysis[];
  attentionFlow: AttentionFlow;
}

interface AttentionInterpretation {
  pattern: 'local' | 'global' | 'syntactic' | 'semantic';
  description: string;
  confidence: number;
  evidenceTokens: TokenEvidence[];
}

class AttentionVisualizationSystem {
  private attentionExtractor: AttentionExtractor;
  private visualizationRenderer: AttentionVisualizationRenderer;
  private patternAnalyzer: AttentionPatternAnalyzer;
  private interactionHandler: InteractionHandler;

  constructor() {
    this.initializeVisualizationComponents();
    this.setupInteractiveVisualization();
  }

  private initializeVisualizationComponents(): void {
    // 注意重み抽出器
    this.attentionExtractor = new AttentionExtractor({
      supportedModels: ['bert', 'gpt', 'transformer', 't5'],
      extractionLayers: 'all', // 'all', 'last', [1, 3, 5]
      includeGradients: true
    });

    // 可視化レンダラー
    this.visualizationRenderer = new AttentionVisualizationRenderer({
      renderingEngine: 'canvas', // 'canvas', 'svg', 'webgl'
      colorScheme: 'viridis',
      animationEnabled: true,
      responsiveDesign: true
    });

    // パターン分析器
    this.patternAnalyzer = new AttentionPatternAnalyzer({
      patternTypes: ['positional', 'syntactic', 'semantic', 'task_specific'],
      clusteringMethod: 'hierarchical',
      significanceThreshold: 0.1
    });

    // インタラクションハンドラー
    this.interactionHandler = new InteractionHandler({
      interactions: ['hover', 'click', 'brush', 'zoom'],
      tooltipEnabled: true,
      selectionEnabled: true
    });
  }

  // マルチモーダル注意可視化
  async visualizeMultiModalAttention(
    model: TransformerModel,
    textInput: string,
    imageInput?: ImageData,
    audioInput?: AudioData
  ): Promise<AttentionVisualizationResult> {
    // 入力の前処理
    const processedInputs = await this.preprocessMultiModalInputs({
      text: textInput,
      image: imageInput,
      audio: audioInput
    });

    // 注意重みの抽出
    const attentionWeights = await this.attentionExtractor.extractAttention(
      model,
      processedInputs
    );

    // モダリティ間注意の分析
    const crossModalAttention = this.analyzeCrossModalAttention(
      attentionWeights,
      processedInputs
    );

    // 注意パターンの分析
    const attentionPatterns = await this.patternAnalyzer.analyzePatterns(
      attentionWeights
    );

    // 可視化要素の生成
    const visualizations = await this.generateVisualizations(
      attentionWeights,
      crossModalAttention,
      attentionPatterns
    );

    return {
      modelId: model.id,
      inputId: this.generateInputId(processedInputs),
      timestamp: new Date(),
      attentionMaps: visualizations.attentionMaps,
      aggregatedAttention: visualizations.aggregatedAttention,
      interpretations: this.generateInterpretations(attentionPatterns),
      interactiveElements: this.createInteractiveElements(visualizations)
    };
  }

  // リアルタイム注意ストリーム可視化
  visualizeAttentionStream(
    modelStream: Observable<ModelPrediction>
  ): Observable<StreamingAttentionVisualization> {
    return modelStream.pipe(
      // バッファリング（スムーズなアニメーション用）
      bufferTime(100),
      filter(buffer => buffer.length > 0),

      // 注意重みの抽出
      mergeMap(predictions => 
        from(predictions).pipe(
          mergeMap(prediction => 
            this.extractAttentionWeights(prediction)
          ),
          toArray()
        )
      ),

      // 時系列注意パターンの分析
      scan((acc, current) => {
        return this.updateTemporalAttentionPatterns(acc, current);
      }, this.initializeTemporalState()),

      // 可視化の生成
      map(temporalState => 
        this.generateStreamingVisualization(temporalState)
      ),

      // フレームレート制御
      throttleTime(16), // 60fps

      share()
    );
  }

  // 注意ヘッド役割分析
  async analyzeAttentionHeadRoles(
    model: TransformerModel,
    dataset: Dataset
  ): Promise<AttentionHeadRoleAnalysis> {
    const headAnalyses = [];

    // 各レイヤーの各ヘッドを分析
    for (let layerIdx = 0; layerIdx < model.numLayers; layerIdx++) {
      for (let headIdx = 0; headIdx < model.numHeads; headIdx++) {
        const headAnalysis = await this.analyzeIndividualHead(
          model,
          layerIdx,
          headIdx,
          dataset
        );
        headAnalyses.push(headAnalysis);
      }
    }

    // ヘッドの機能分類
    const functionalClusters = this.clusterHeadsByFunction(headAnalyses);

    // 冗長性分析
    const redundancyAnalysis = this.analyzeHeadRedundancy(headAnalyses);

    // 重要度ランキング
    const importanceRanking = this.rankHeadsByImportance(headAnalyses);

    return {
      headAnalyses,
      functionalClusters,
      redundancyAnalysis,
      importanceRanking,
      recommendations: this.generateOptimizationRecommendations(
        functionalClusters,
        redundancyAnalysis
      )
    };
  }

  // 個別ヘッドの分析
  private async analyzeIndividualHead(
    model: TransformerModel,
    layerIdx: number,
    headIdx: number,
    dataset: Dataset
  ): Promise<IndividualHeadAnalysis> {
    // 注意パターンの収集
    const attentionPatterns = await this.collectAttentionPatterns(
      model,
      layerIdx,
      headIdx,
      dataset
    );

    // 位置的パターンの分析
    const positionalPatterns = this.analyzePositionalPatterns(
      attentionPatterns
    );

    // 構文的パターンの分析
    const syntacticPatterns = this.analyzeSyntacticPatterns(
      attentionPatterns,
      dataset
    );

    // 意味的パターンの分析
    const semanticPatterns = this.analyzeSemanticPatterns(
      attentionPatterns,
      dataset
    );

    // ヘッド機能の分類
    const functionClassification = this.classifyHeadFunction({
      positionalPatterns,
      syntacticPatterns,
      semanticPatterns
    });

    return {
      layerIndex: layerIdx,
      headIndex: headIdx,
      functionClassification,
      positionalPatterns,
      syntacticPatterns,
      semanticPatterns,
      confidence: this.calculateAnalysisConfidence({
        positionalPatterns,
        syntacticPatterns,
        semanticPatterns
      })
    };
  }

  // インタラクティブ注意探索
  createInteractiveAttentionExplorer(
    attentionData: AttentionVisualizationResult
  ): InteractiveAttentionExplorer {
    const explorer = new InteractiveAttentionExplorer({
      container: this.createVisualizationContainer(),
      data: attentionData,
      interactions: {
        tokenSelection: true,
        layerNavigation: true,
        headComparison: true,
        patternHighlighting: true
      }
    });

    // インタラクションイベントの設定
    this.setupExplorerInteractions(explorer);

    return explorer;
  }

  private setupExplorerInteractions(
    explorer: InteractiveAttentionExplorer
  ): void {
    // トークン選択時の処理
    explorer.onTokenSelect$.subscribe(selectedToken => {
      const relatedAttentions = this.findRelatedAttentions(
        selectedToken,
        explorer.data
      );
      explorer.highlightRelatedElements(relatedAttentions);
    });

    // レイヤー変更時の処理
    explorer.onLayerChange$.subscribe(layerIndex => {
      const layerData = this.getLayerData(layerIndex, explorer.data);
      explorer.updateVisualization(layerData);
    });

    // ヘッド比較時の処理
    explorer.onHeadComparison$.subscribe(({ head1, head2 }) => {
      const comparisonAnalysis = this.compareAttentionHeads(head1, head2);
      explorer.displayComparison(comparisonAnalysis);
    });

    // パターンハイライト時の処理
    explorer.onPatternHighlight$.subscribe(pattern => {
      const matchingElements = this.findPatternMatches(
        pattern,
        explorer.data
      );
      explorer.highlightPattern(matchingElements);
    });
  }

  // 注意重み分析レポート生成
  async generateAttentionAnalysisReport(
    attentionData: AttentionVisualizationResult[]
  ): Promise<AttentionAnalysisReport> {
    // 統計的分析
    const statisticalAnalysis = this.performStatisticalAnalysis(
      attentionData
    );

    // パターン頻度分析
    const patternFrequency = this.analyzePatternFrequency(attentionData);

    // 異常パターンの検出
    const anomalyDetection = this.detectAnomalousAttentionPatterns(
      attentionData
    );

    // パフォーマンス相関分析
    const performanceCorrelation = await this.analyzePerformanceCorrelation(
      attentionData
    );

    // 改善提案の生成
    const improvementSuggestions = this.generateImprovementSuggestions({
      statisticalAnalysis,
      patternFrequency,
      anomalyDetection,
      performanceCorrelation
    });

    return {
      executiveSummary: this.generateExecutiveSummary({
        statisticalAnalysis,
        patternFrequency,
        performanceCorrelation
      }),
      detailedAnalysis: {
        statisticalAnalysis,
        patternFrequency,
        anomalyDetection,
        performanceCorrelation
      },
      visualizations: this.generateReportVisualizations(attentionData),
      improvementSuggestions,
      confidence: this.calculateReportConfidence({
        statisticalAnalysis,
        patternFrequency,
        performanceCorrelation
      })
    };
  }
}

// 結果インターフェース
interface AttentionHeadRoleAnalysis {
  headAnalyses: IndividualHeadAnalysis[];
  functionalClusters: FunctionalCluster[];
  redundancyAnalysis: RedundancyAnalysis;
  importanceRanking: HeadImportanceRanking[];
  recommendations: OptimizationRecommendation[];
}

interface InteractiveAttentionExplorer {
  container: HTMLElement;
  data: AttentionVisualizationResult;
  onTokenSelect$: Observable<SelectedToken>;
  onLayerChange$: Observable<number>;
  onHeadComparison$: Observable<HeadComparison>;
  onPatternHighlight$: Observable<AttentionPattern>;
  highlightRelatedElements(elements: RelatedElement[]): void;
  updateVisualization(data: LayerVisualizationData): void;
  displayComparison(analysis: ComparisonAnalysis): void;
  highlightPattern(elements: PatternElement[]): void;
}

interface AttentionAnalysisReport {
  executiveSummary: ExecutiveSummary;
  detailedAnalysis: DetailedAnalysis;
  visualizations: ReportVisualization[];
  improvementSuggestions: ImprovementSuggestion[];
  confidence: number;
}

// 統合説明可能状況認識システム
interface ExplainableSituationalAwarenessResult {
  situationAssessment: SituationAssessment;
  explanation: ComprehensiveExplanation;
  visualizations: ExplanationVisualization[];
  interactiveElements: InteractiveExplanationElement[];
  trustMetrics: TrustMetrics;
  auditTrail: AuditTrail;
}

interface SituationAssessment {
  currentSituation: SituationState;
  riskLevel: RiskLevel;
  predictions: SituationPrediction[];
  recommendations: ActionRecommendation[];
  confidence: number;
}

interface ComprehensiveExplanation {
  overallExplanation: string;
  componentExplanations: ComponentExplanation[];
  causalChain: CausalLink[];
  uncertaintyFactors: UncertaintyFactor[];
  alternativeScenarios: AlternativeScenario[];
}

class ExplainableSituationalAwarenessSystem {
  private situationAnalyzer: SituationAnalyzer;
  private explanationEngine: ComprehensiveExplanationEngine;
  private visualizationSystem: ExplanationVisualizationSystem;
  private auditingSystem: AuditingSystem;
  private trustCalculator: TrustCalculator;

  constructor() {
    this.initializeExplainableSystem();
    this.setupAuditTrail();
  }

  private initializeExplainableSystem(): void {
    // 状況分析エンジン
    this.situationAnalyzer = new SituationAnalyzer({
      analysisModules: [
        new ImageAnalysisModule(),
        new TextAnalysisModule(),
        new SensorDataModule(),
        new TemporalAnalysisModule()
      ],
      explainabilityRequired: true
    });

    // 包括的説明エンジン
    this.explanationEngine = new ComprehensiveExplanationEngine({
      explainers: [
        new SHAPExplainer(),
        new LIMEExplainer(),
        new AttentionExplainer(),
        new CausalExplainer()
      ],
      integrationStrategy: 'consensus_weighted',
      naturalLanguageGenerator: new NLGEngine()
    });

    // 可視化システム
    this.visualizationSystem = new ExplanationVisualizationSystem({
      chartTypes: ['waterfall', 'heatmap', 'network', 'timeline'],
      interactivity: true,
      accessibility: true
    });

    // 監査システム
    this.auditingSystem = new AuditingSystem({
      logLevel: 'detailed',
      retention: '7years',
      compliance: ['GDPR', 'HIPAA', 'SOX']
    });

    // 信頼度計算器
    this.trustCalculator = new TrustCalculator({
      metrics: ['consistency', 'stability', 'fidelity', 'completeness'],
      aggregationMethod: 'weighted_average'
    });
  }

  // 説明可能状況認識の実行
  async analyzeSituationWithExplanation(
    multiModalInput: MultiModalInput,
    userContext: UserContext
  ): Promise<ExplainableSituationalAwarenessResult> {
    // 監査ログの開始
    const sessionId = this.auditingSystem.startSession({
      userId: userContext.userId,
      timestamp: new Date(),
      inputHash: this.generateInputHash(multiModalInput)
    });

    try {
      // 状況分析の実行
      const situationAssessment = await this.situationAnalyzer.analyze(
        multiModalInput,
        { explainabilityEnabled: true }
      );

      // 包括的説明の生成
      const explanation = await this.explanationEngine.generateExplanation(
        situationAssessment,
        multiModalInput,
        userContext
      );

      // 可視化の生成
      const visualizations = await this.visualizationSystem.createVisualizations(
        situationAssessment,
        explanation,
        userContext.preferences
      );

      // インタラクティブ要素の生成
      const interactiveElements = this.createInteractiveElements(
        situationAssessment,
        explanation,
        visualizations
      );

      // 信頼度指標の計算
      const trustMetrics = await this.trustCalculator.calculateTrust(
        situationAssessment,
        explanation
      );

      // 監査証跡の生成
      const auditTrail = this.auditingSystem.generateAuditTrail(sessionId);

      const result = {
        situationAssessment,
        explanation,
        visualizations,
        interactiveElements,
        trustMetrics,
        auditTrail
      };

      // 結果の記録
      this.auditingSystem.logResult(sessionId, result);

      return result;

    } catch (error) {
      // エラーの記録
      this.auditingSystem.logError(sessionId, error);
      throw error;
    } finally {
      // セッションの終了
      this.auditingSystem.endSession(sessionId);
    }
  }

  // 対話的説明セッション
  createInteractiveExplanationSession(
    initialResult: ExplainableSituationalAwarenessResult
  ): Observable<InteractiveExplanationResponse> {
    return new Observable<InteractiveExplanationResponse>(observer => {
      const session = new InteractiveExplanationSession({
        initialResult,
        explanationEngine: this.explanationEngine,
        visualizationSystem: this.visualizationSystem
      });

      // ユーザークエリのストリーム処理
      session.userQueries$.pipe(
        // クエリの分析
        map(query => this.analyzeUserQuery(query)),

        // 説明の生成
        mergeMap(analyzedQuery => 
          this.generateTargetedExplanation(
            analyzedQuery,
            initialResult
          )
        ),

        // 可視化の更新
        map(explanation => 
          this.updateVisualizationsForQuery(explanation)
        )
      ).subscribe(
        response => observer.next(response),
        error => observer.error(error)
      );

      return () => session.destroy();
    });
  }

  // 説明の有効性検証
  async validateExplanationEffectiveness(
    explanation: ComprehensiveExplanation,
    userFeedback: UserFeedback[]
  ): Promise<ExplanationValidationResult> {
    // ユーザー理解度の分析
    const comprehensionAnalysis = this.analyzeUserComprehension(
      userFeedback
    );

    // 説明の客観的品質評価
    const objectiveQuality = await this.assessObjectiveQuality(
      explanation
    );

    // 信頼度の変化追跡
    const trustEvolution = this.trackTrustEvolution(
      userFeedback
    );

    // 行動変化の分析
    const behaviorImpact = this.analyzeBehaviorImpact(
      userFeedback
    );

    return {
      comprehensionScore: comprehensionAnalysis.score,
      objectiveQualityScore: objectiveQuality.score,
      trustScore: trustEvolution.finalScore,
      behaviorImpactScore: behaviorImpact.score,
      overallEffectiveness: this.calculateOverallEffectiveness({
        comprehensionAnalysis,
        objectiveQuality,
        trustEvolution,
        behaviorImpact
      }),
      recommendations: this.generateImprovementRecommendations({
        comprehensionAnalysis,
        objectiveQuality,
        trustEvolution,
        behaviorImpact
      })
    };
  }
}

// ユーティリティクラス
class ExplanationVisualizationSystem {
  createDashboard(
    result: ExplainableSituationalAwarenessResult
  ): ExplanationDashboard {
    const dashboard = new ExplanationDashboard({
      layout: 'responsive_grid',
      components: [
        this.createSituationOverview(result.situationAssessment),
        this.createExplanationSummary(result.explanation),
        this.createTrustIndicator(result.trustMetrics),
        this.createInteractiveExplorer(result.interactiveElements)
      ]
    });

    return dashboard;
  }

  private createSituationOverview(
    assessment: SituationAssessment
  ): SituationOverviewComponent {
    return new SituationOverviewComponent({
      currentState: assessment.currentSituation,
      riskVisualization: this.createRiskVisualization(assessment.riskLevel),
      predictionsTimeline: this.createPredictionsTimeline(assessment.predictions),
      recommendationsPanel: this.createRecommendationsPanel(assessment.recommendations)
    });
  }

  private createExplanationSummary(
    explanation: ComprehensiveExplanation
  ): ExplanationSummaryComponent {
    return new ExplanationSummaryComponent({
      mainExplanation: explanation.overallExplanation,
      causalChain: this.visualizeCausalChain(explanation.causalChain),
      uncertaintyIndicators: this.createUncertaintyIndicators(explanation.uncertaintyFactors),
      alternativeScenarios: this.createScenarioComparison(explanation.alternativeScenarios)
    });
  }
}